In every aspect of our lives, key factors change over time. When we visualize these trends, previously hidden patterns jump into view. Those who take the time to remember the past in this way are better able to shape their future destiny.

Thursday, January 19, 2006

Employment Metrics: There Must Be A Better Way.

In the previous post, we listed 51 employment related metrics that we had unearthed by briefly digging into a short list of press and blog coverage of the most recent Bureau of Labor Statistics Employment Report (for December 2005).

Observations:

A. Amazingly, many factors are offered and used in the logical arguments of the story or blog entry without providing any data at all to back up whatever claims are made

B. Some authors relied on emotional language instead of numeric quantification to make their points

C. Only a small percentage of the commentators that I have read used any graphs at all. The graphs that were used covered widely different time periods, 3 years, 7 years, 11 years, 65 years with no explanation of why a particular interval was chosen.

D. A large percentage of the factors that came with some associated data looked only at the single data point showing the value for the most recent month. E.g. the number of jobs of particular type added in December 2005.

E. Some factors came with two data points - the values for the two most recent months

F. One case used a single data point that was the average of the two most recent months

G. Several cases gave average values for the full years 2004 and 2005.

H. Some factors indicated whether they represented seasonally adjusted values or not. Many other factors were offered with any such indication.

I. Some factors were raw counts, others involved year over year differences in the counts, still others showed year over year percentage change or month over month percentage change, or month over month change in the counts, and with or without the moving average.

J. Few commentaries gave you the data itself.

K. Many of the commentaries seemed to be in a terrific hurry to publish within a short time after the BLS monthly release on Friday, January 6th. We are now almost two weeks out and it will be another two weeks till the next release. All the BLS data showing the trends for the past 65 years is already posted and waiting our actions aimed at understanding the most recent month in light of what has happened over the years. The plan of this blog is to try to use that time wisely and see if we can bring some further clarity to what's going on.

How can we make sense of all this?

Conclusion: There must be a better way.

In the next post, we will entertain a few suggestions that may help lead us out of this inhospitable wilderness.

Trend Visualization Principles

1. Context Comes First. Ask all the subject matter experts: What are the most important factors? What's missing? What other factors must you include?

2.Create a History. Measure, record and archive a trend history of every important factor. For best results, measure at a relatively high frequency.

3. Look at ALL the Data. Once you have a history of the most important factors, you'll find charts with but a single variable will tell a powerful story all by themselves. Avoid beginning with the most complicated, most cluttered charts before you have established a good context by actually looking at each important factor on its own.

4. Share ALL Your Data. When you publish a chart, share the readily reusable data with the chart. Include the entire time range of the data you analyzed even if the charts you presented use a shorter interval.

6. Show Your Thinking. Place explanatory text for your findings in close physical proximity to the your published trend charts. Data + Charts + Text creates a full package that encourages further conversation.

7. Insure Readability. Make sure the axes and titles and other text graphics are easily readable.

What principles do you see as contributing most to improved understanding and enhanced collaboration?